Method and apparatus for ordering results of a query

Abstract

A method and apparatus for ordering results from a query is provided herein. During operation, a spoken query is received and converted to a textual representation, such as a word lattice. Search strings are then created from the word lattice. For example a set search strings may be created from the N-grams, such as unigrams and bigrams, of the word lattice. The search strings may be ordered and truncated based on confidence values assigned to the n-grams by the speech recognition system. The set of search strings are sent to at least one search engine, and search results are obtained. The search results are then re-arranged or reordered based on a semantic similarity between the search results and the word lattice.

1 . A method for reordering search results obtained from a search engine, the method comprising the steps of:
 receiving speech;   creating a word lattice from the received speech;   creating a query vector comprising search strings from the word lattice;   sending the search strings to a search engine;   receiving search results from the search engine;   reordering the search results based on a semantic similarity between the search results and the word lattice.   
     
     
         2 . The method of  claim 1  wherein the step of receiving speech comprises the step of receiving a spoken query. 
     
     
         3 . The method of  claim 1  wherein the word lattice comprises a weighted graph of word hypotheses derived from the spoken input. 
     
     
         4 . The method of  claim 1  wherein the search strings comprise N-grams, unigrams, and bigrams of the word lattice output of the speech-to-text conversion system. 
     
     
         5 . The method of  claim 1  wherein the search engine comprises a web-based search engine. 
     
     
         6 . The method of  claim 1  wherein the search engine comprises a search engine that searches locally-stored files. 
     
     
         7 . The method of  claim 1  wherein the step of reordering the search results comprises the steps of:
 creating a term-document matrix (A) that contains sentences with the search strings, obtained from the word lattice, for each returned document; 
 performing a single-value decomposition on the term-document matrix to produce a subspace document matrix (D) containing subspace document vectors, wherein D corresponds to A in that the columns of D represent “term weights” for each document within A; 
 obtaining confidence values q=(c 1 , c 2 , . . . , cN) of N search strings within the query vector; 
 finding a distances between q and the subspace document vectors; and 
 reordering the search results based on the distances between q and the subspace document vectors. 
 
     
     
         8 . A method for reordering search results obtained from a search engine, the method comprising the steps of:
 creating a query vector comprising search strings from a word lattice created from spoken words;   sending the search strings to a search engine;   receiving search results from the search engine;   reordering the search results based on a semantic similarity between the search results and the word lattice.   
     
     
         9 . The method of  claim 8  further comprising the step of receiving speech. 
     
     
         10 . The method of  claim 8  wherein the word lattice comprises a weighted graph of word hypotheses derived from the spoken input. 
     
     
         11 . The method of  claim 8  wherein the search strings comprise N-grams, unigrams, and bigrams of the word lattice output of the speech-to-text conversion system. 
     
     
         12 . The method of  claim 8  wherein the search engine comprises a web-based search engine. 
     
     
         13 . The method of  claim 8  wherein the search engine comprises a search engine that searches locally-stored files. 
     
     
         14 . The method of  claim 8  wherein the step of reordering the search results comprises the steps of:
 creating a term-document matrix (A) that contains sentences with the search strings, obtained from the word lattice, for each returned document; 
 performing a single-value decomposition on the term-document matrix to produce a subspace document matrix (D) containing subspace document vectors, wherein D corresponds to A in that the columns of D represent “term weights” for each document within A; 
 obtaining confidence values q=(c 1 , c 2 , . . . , cN) of N search strings within the query vector; 
 finding a distances between q and the subspace document vectors; and 
 reordering the search results based on the distances between q and the subspace document vectors. 
 
     
     
         15 . An apparatus for reordering search results, the apparatus comprising:
 logic circuitry creating a query vector comprising search strings from a word lattice, the logic circuitry sending the search strings to a search engine, receiving search results from the search engine, and reordering the search results based on a semantic similarity between the search results and the word lattice.   
     
     
         16 . The apparatus of  claim 15  wherein the word lattice comprises a weighted graph of word hypotheses derived from the spoken input. 
     
     
         17 . The apparatus of  claim 15  wherein the search strings comprise N-grams, unigrams, and bigrams of the word lattice output of the speech-to-text conversion system. 
     
     
         18 . The apparatus of  claim 15  wherein the search engine comprises a web-based search engine. 
     
     
         19 . The apparatus of  claim 15  wherein the search engine comprises a search engine that searches locally-stored files. 
     
     
         20 . The apparatus of  claim 15  wherein the step of reordering the search results comprises the steps of:
 creating a term-document matrix (A) that contains sentences with the search strings, obtained from the word lattice, for each returned document; 
 performing a single-value decomposition on the term-document matrix to produce a subspace document matrix (D) containing subspace document vectors, wherein D corresponds to A in that the columns of D represent “term weights” for each document within A; 
 obtaining confidence values q=(c 1 , c 2 , . . . , cN) of N search strings within the query vector; 
 finding a distances between q and the subspace document vectors; and 
 reordering the search results based on the distances between q and the subspace document vectors.